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A New Clustering Methodology for the Analysis of Sorted or Categorized Stimuli

Author
Desarbo, Wayne S.; Jedidi, Kamel; Johnson, Michael D.
Abstract
This paper introduces a new stochastic clustering methodology devised for the analysis of categorized or sorted data. The methodology reveals consumers' common category knowledge as well as individual differences in using this knowledge for classifying brands in a designated product class. A small study involving the categorization of 28 brands of U.S. automobiles is presented where the results of the proposed methodology are compared with those obtained from KMEANS clustering. Finally, directions for future research are discussed.
Date Issued
1991-08-01Subject
cluster analysis; categorization; sorting tasks; maximum likelihood estimation
Related DOI:
https://doi.org/10.1007/BF02404077Rights
Required Publisher Statement: © Springer. Final version published as: Desarbo, W. S., Jedidi, K., & Johnson, M. D. (1991). A new clustering methodology for the analysis of sorted or categorized stimuli. Marketing Letters, 2(3), 267–279. Reprinted with permission. All rights reserved.
Type
article